This satellite map of city lights shows the dense populations along Brazil’s southeast coast. The brightly lit cities of Rio de Janeiro, São Paulo, and Porto Alegre stand out most prominently. (NASA image by Robert Simmon, based on MODIS Blue Marble and Defense Meteorological Satellite Program city lights data.)

This satellite map of city lights shows the dense populations along Brazil’s southeast coast. The brightly lit cities of Rio de Janeiro, São Paulo, and Porto Alegre stand out most prominently. (NASA image by Robert Simmon, based on MODIS Blue Marble and Defense Meteorological Satellite Program city lights data.)
How to Catch the Breeze?
So, the topic had been easy. The problem was finding data to support his hunch that offshore wind had great potential in Brazil. To determine how much wind energy can be generated over coastal waters, Willett Kempton and Richard Garvine (who taught the technical and scientific aspects of Pimenta’s class) had shown their students how to estimate wind speeds 80 to 100 meters off the surface of the ocean, where a turbine’s massive blades would spin. Starting with wind speeds recorded by meteorological buoys near the ocean’s surface, students extrapolated wind speeds using a mathematical equation that describes winds at different heights in the atmosphere.
From there, he intended to calculate how much energy could be produced with a General Electric 3.6s Offshore turbine and the REpower Systems 5M turbine. The companies had released detailed information about the amount of power each type of turbine would produce at a variety of wind speeds. To estimate how much electricity Brazil could expect to generate using existing technology, he just had to know the wind speed.

NASA’s QuikSCAT satellite measures wind speed and direction over the ocean. This map shows the average winds in January. Pale blue indicates light winds, while red indicates strong winds. Arrows indicate direction. (NASA map by Robert Simmon, based on the Scatterometer Climatology of Ocean Winds.)

NASA’s QuikSCAT satellite measures wind speed and direction over the ocean. This map shows the average winds in January. Pale blue indicates light winds, while red indicates strong winds. Arrows indicate direction. (NASA map by Robert Simmon, based on the Scatterometer Climatology of Ocean Winds.)
“QuikSCAT data is well known among physical oceanographers,” says Pimenta. Scientists at NASA’s Jet Propulsion Laboratory had been creating satellite-based maps of winds over the world’s oceans since QuikSCAT’s launch in 1999. At the same time that Pimenta was working on his offshore wind research, Timothy Liu, Wenqing Tang, and Xiaosu Xie, all of the Jet Propulsion Laboratory, were using QuikSCAT measurements to estimate the amount of energy that could, in theory, be generated from ocean winds. Wind data had even been part of a suite of NASA products that fed into RETScreen software, a free program used to estimate clean energy potential. (See Power to the People on the Earth Observatory.) But as far as he knew, no one had done a practical estimate of the amount of power that would be produced with existing turbine technology using QuikSCAT data.
Measuring Ocean Winds from Space
Pimenta’s professor Willett Kempton pointed out two limitations with QuikSCAT’s measurements of wind speed. First, the satellite only measures winds in any given place once per day, far less information than buoys provide. “With buoy data, you can get down to five-minute or even one-minute time resolution,” says Kempton. Since winds are variable, power companies need to know how frequently they can expect lulls when power can’t be produced and how long those lulls might be.

NASA scientists used satellite wind measurements to estimate the available wind energy over the ocean, called power density. Blue represents areas with little potential wind power, red indicates locations with high potential for power. To be cost-effective, offshore wind farms must be located near population centers in shallow waters with high power density. (NASA image created by Jesse Allen, using QuikSCAT data from Timothy Liu, Wenqing Tang, and Xiaosu Xie, NASA/JPL.)

NASA scientists used satellite wind measurements to estimate the available wind energy over the ocean, called power density. Blue represents areas with little potential wind power, red indicates locations with high potential for power. To be cost-effective, offshore wind farms must be located near population centers in shallow waters with high power density. (NASA image created by Jesse Allen, using QuikSCAT data from Timothy Liu, Wenqing Tang, and Xiaosu Xie, NASA/JPL.)

“Eventually, we just tried QuikSCAT,” says Pimenta. He compared QuikSCAT measurements of wind speed to measurements taken at the same time by the one buoy that had been in operation during the QuikSCAT record. The two matched reasonably well—close enough, his professor told him, to do a first estimate of the power potential. He extrapolated QuikSCAT measurements of wind speeds at 10 meters above the surface of the ocean to wind speeds 80 to 100 meters up, the height of the wind turbine’s hub. He calculated the amount of power existing turbines would produce at those speeds, and then averaged these measurements to get an estimate of power production throughout the year. In the end, he came up with a map of turbine power output for a wide swath of coastal waters off southeast Brazil.

Pimenta compared measurements of wind speed measured by a buoy (blue line) with satellite data (purple dots) to confirm the accuracy of QuikSCAT. (Graph adapted from Pimenta et al., 2008.)
Southeast Brazil’s Offshore Potential
But knowing how much power the winds could provide was not enough to make a practical estimate of the wind potential of the area. Pimenta also had to know how many turbines could actually be built off the Brazilian coast. Wind farms can’t be built in shipping lanes or bird flyways or near scenic coastlines. Current turbine technology can’t be installed in waters deeper than 50 meters, though companies are beginning to invest in floating turbines. Pimenta superimposed the wind data onto a map of the ocean floor to identify suitable locations for wind farms. This allowed him to calculate how many turbines could be installed off the southeast coast of Brazil. If the suitable areas were fully developed with existing technology, Pimenta estimated that offshore wind farms could produce 102 gigawatts of power on average. Brazil’s average national power need in 2008 was about 100 gigawatts.

Current offshore wind turbines must be in water no more than 50 meters deep. Pimenta combined his estimates of wind power density at 80 meters above the surface with ocean depth measurements (blue lines) to find nearshore areas with high winds and shallow water. His analysis shows a promising location for a wind farm near the city of Porta Alegre, Brazil. (NASA map by Robert Simmon, based on data from Felipe Pimenta.)

Current offshore wind turbines must be in water no more than 50 meters deep. Pimenta combined his estimates of wind power density at 80 meters above the surface with ocean depth measurements (blue lines) to find nearshore areas with high winds and shallow water. His analysis shows a promising location for a wind farm near the city of Porta Alegre, Brazil. (NASA map by Robert Simmon, based on data from Felipe Pimenta.)
After turning in his final project, Pimenta published his results in Renewable Energy in June 2008. No one has contacted him yet about developing an offshore wind farm in Brazil, but the possibility is real. It has happened to other students who have taken Kempton’s course. “A developer decided where to site a billion dollar plus project based on data that was produced in one of our classes,” says Kempton. “We have some very good students. I show them how to do it and let them go.”
1. References
2. Liu, W.T., Tang, W., Xie, X. (2008, July 8) Wind power distribution over the ocean. Geophysical Research Letters, 35, L13808.
3. Ogier, T. (2001, May 7). Did Brazil’s lights just flicker? Business Week. Accessed January 14, 2009.
4. Pimenta, F., Kempton, W., Garvine, R. (2008, June 9). Combining meteorological stations and satellite data to evaluate the offshore wind power resource of Southeastern Brazil. Renewable Energy, 33(11), 2375-2387.
5. Renfrow, S. (2008, August 18). The power of a Brazilian wind. Sensing our planet: NASA Earth Science Research Features 2008. NASA Earth System Science Data and Services. Accessed January 14, 2009.
6. StatoilHydro. The world’s first full-scale floating windmill. Accessed January 14, 2009.
7. Svenvold, M. (2008, September 12) Wind-power politics. The New York Times Magazine. Accessed January 14, 2009.
• Further Reading
• Herring, D. Power to the People. NASA’s Earth Observatory. Accessed January 14, 2009.
• Jet Propulsion Laboratory. Winds: Measuring ocean winds from space. NASA. Accessed January 14, 2009.
• RETScreen International.
• Riebeek, H. (2008, July 16). Global ocean wind energy potential. NASA’s Earth Observatory. Accessed January 14, 2009.
• University of Delaware. (2008). Offshore wind power. Accessed January 14, 2009.